Machine learning–based prediction of rotator cuff tears using anatomical parameters: a retrospective cohort study
Abstract Background To apply machine learning to improve risk assessment for rotator cuff tears by developing an integrated predictive model that combines acromial morphology (structural factors) and patient characteristics (systemic factors). Methods A total of 342 patients who underwent shoulder r...
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| Автори: | , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
BMC
2026-03-01
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| Серія: | BMC Musculoskeletal Disorders |
| Предмети: | |
| Онлайн доступ: | https://doi.org/10.1186/s12891-026-09765-2 |
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